2013 – Page 12 – American ME and CFS Society

Article on CFS does not reflect current best treatment practices

TO THE EDITOR: We feel that the overview of the diagnosis and treatment of chronic fatigue syndrome (CFS) was incomplete and did not reflect current best treatment practices. The discussion of current CFS research omitted key studies, such as evidence from prospective cohort studies indicating that up to 10 percent of patients with postinfectious syndromes develop CFS, regardless of the type of infectious agent.1 Biomarker research has shown distinct patterns of gene expression correlating with cytokine, adrenergic, and sensory receptor changes after modest exercise in patients with CFS compared with healthy sedentary patients.2 Indeed, many peer-reviewed publications support a physiologic etiology of CFS.

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Comment on: Chronic fatigue syndrome: diagnosis and treatment. [Am Fam Physician. 2012]

Source: Bateman L, Spotila J. Article on CFS does not reflect current best treatment practices. Am Fam Physician. 2013 Apr 1;87(7):Online. http://www.aafp.org/afp/2013/0401/ol1.html (Full article)

Treatment outcome in adults with chronic fatigue syndrome: a prospective study in England based on the CFS/ME National Outcomes Database

Erratum in: QJM. 2013 Jun;106(6):567.

Abstract:

BACKGROUND: Chronic fatigue syndrome (CFS) is relatively common and disabling. Over 8000 patients attend adult services each year, yet little is known about the outcome of patients attending NHS services.

AIM: Investigate the outcome of patients with CFS and what factors predict outcome.

DESIGN: Longitudinal patient cohort.

METHODS: We used data from six CFS/ME (myalgic encephalomyelitis) specialist services to measure changes in fatigue (Chalder Fatigue Scale), physical function (SF-36), anxiety and depression (Hospital Anxiety and Depression Scale) and pain (visual analogue pain rating scale) between clinical assessment and 8-20 months of follow-up. We used multivariable linear regression to investigate baseline factors associated with outcomes at follow-up.

RESULTS: Baseline data obtained at clinical assessment were available for 1643 patients, of whom 834 (51%) had complete follow-up data. There were improvements in fatigue [mean difference from assessment to outcome: -6.8; 95% confidence interval (CI) -7.4 to -6.2; P < 0.001]; physical function (4.4; 95% CI 3.0-5.8; P < 0.001), anxiety (-0.6; 95% CI -0.9 to -0.3; P < 0.001), depression (-1.6; 95% CI -1.9 to -1.4; P < 0.001) and pain (-5.3; 95% CI -7.0 to -3.6; P < 0.001). Worse fatigue, physical function and pain at clinical assessment predicted a worse outcome for fatigue at follow-up. Older age, increased pain and physical function at assessment were associated with poorer physical function at follow-up.

CONCLUSION: Patients who attend NHS specialist CFS/ME services can expect similar improvements in fatigue, anxiety and depression to participants receiving cognitive behavioural therapy and graded exercise therapy in a recent trial, but are likely to experience less improvement in physical function. Outcomes were predicted by fatigue, disability and pain at assessment.

Comment in: RE: ‘Treatment outcome in adults with chronic fatigue syndrome: a prospective study. [QJM. 2014]

Source: Crawley E, Collin SM, White PD, Rimes K, Sterne JA, May MT; CFS/ME National Outcomes Database. Treatment outcome in adults with chronic fatigue syndrome: a prospective study in England based on the CFS/ME National Outcomes Database. QJM. 2013 Jun;106(6):555-65. doi: 10.1093/qjmed/hct061. Epub 2013 Mar 28. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3665909/ (Full article)

Cognitive deficits in chronic fatigue syndrome and their relationship to psychological status, symptomatology, and everyday functioning

Abstract:

OBJECTIVE: To examine cognitive deficits in people with chronic fatigue syndrome (CFS) and their relationship to psychological status, CFS symptoms, and everyday functioning.

METHOD: The current study compared the cognitive performance (reaction time, attention, memory, motor functioning, verbal abilities, and visuospatial abilities) of a sample with CFS (n = 50) with that of a sample of healthy controls (n = 50), all of whom had demonstrated high levels of effort and an intention to perform well, and examined the extent to which psychological status, CFS symptoms, and everyday functioning were related to cognitive performance.

RESULTS: The CFS group showed impaired information processing speed (reaction time), relative to the controls, but comparable performance on tests of attention, memory, motor functioning, verbal ability, and visuospatial ability. Moreover, information processing speed was not related to psychiatric status, depression, anxiety, the number or severity of CFS symptoms, fatigue, sleep quality, or everyday functioning.

CONCLUSION: A slowing in information processing speed appears to be the main cognitive deficit seen in persons with CFS whose performance on effort tests is not compromised. Importantly, this slowing does not appear to be the consequence of other CFS-related variables, such as depression and fatigue, or motor speed.

Source: Cockshell SJ, Mathias JL. Cognitive deficits in chronic fatigue syndrome and their relationship to psychological status, symptomatology, and everyday functioning. Neuropsychology. 2013 Mar;27(2):230-42. doi: 10.1037/a0032084. https://www.ncbi.nlm.nih.gov/pubmed/23527651

Screening NK-, B- and T-cell phenotype and function in patients suffering from Chronic Fatigue Syndrome

Abstract:

BACKGROUND: Chronic Fatigue Syndrome (CFS) is a debilitating neuro-immune disorder of unknown etiology diagnosed by an array of clinical manifestations. Although several immunological abnormalities have been described in CFS, their heterogeneity has limited diagnostic applicability.

METHODS: Immunological features of CFS were screened in 22 CFS diagnosed individuals fulfilling Fukuda criteria and 30 control healthy individuals. Peripheral blood T, B and NK cell function and phenotype were analyzed by flow cytometry in both groups.

RESULTS: CFS diagnosed individuals showed similar absolute numbers of T, B and NK cells, with minor differences in the percentage of CD4+ and CD8+ T cells. B cells showed similar subset frequencies and proliferative responses between groups. Conversely, significant differences were observed in T cell subsets. CFS individuals showed increased levels of T regulatory cells (CD25+/FOXP3+) CD4 T cells, and lower proliferative responses in vitro and in vivo. Moreover, CD8 T cells from the CFS group showed significantly lower activation and frequency of effector memory cells. No clear signs of T-cell immunosenescence were observed. NK cells from CFS individuals displayed higher expression of NKp46 and CD69 but lower expression of CD25 in all NK subsets defined. Overall, T cell and NK cell features clearly clustered CFS individuals.

CONCLUSIONS: Our findings suggest that alterations in T-cell phenotype and proliferative response along with the specific signature of NK cell phenotype may be useful to identify CFS individuals. The striking down modulation of T cell mediated immunity may help to understand intercurrent viral infections in CFS.

Source: Curriu M, Carrillo J, Massanella M, Rigau J, Alegre J, Puig J, Garcia-Quintana AM, Castro-Marrero J, Negredo E, Clotet B, Cabrera C, Blanco J. Screening NK-, B- and T-cell phenotype and function in patients suffering from Chronic Fatigue Syndrome. J Transl Med. 2013 Mar 20;11:68. doi: 10.1186/1479-5876-11-68. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3614537/ (Full article)

Heart rate variability during sleep and subsequent sleepiness in patients with chronic fatigue syndrome

Abstract:

We determined whether alterations in heart rate dynamics during sleep in patients with chronic fatigue syndrome (CFS) differed from controls and/or correlated with changes of sleepiness before and after a night in the sleep laboratory. We compared beat-to-beat RR intervals (RRI) during nocturnal sleep, sleep structure, and subjective scores on visual analog scale for sleepiness in 18 CFS patients with 19 healthy controls aged 25-55 after excluding subjects with sleep disorders. A short-term fractal scaling exponent (α1) of RRI dynamics, analyzed by the detrended fluctuation analysis (DFA) method, was assessed after stratifying patients into those who reported more or less sleepiness after the night’s sleep (a.m. sleepier or a.m. less sleepy, respectively).

Patients in the a.m. sleepier group showed significantly (p<0.05) higher fractal scaling index α1 during non-rapid eye movement (non-REM) sleep (Stages 1, 2, and 3 sleep) than healthy controls, although standard polysomnographic measures did not differ between the groups. The fractal scaling index α1 during non-REM sleep was significantly (p<0.05) higher than that during awake periods after sleep onset for healthy controls and patients in the a.m. less sleepy group, but did not differ between sleep stages for patients in the a.m. sleepier group. For patients, changes in self-reported sleepiness before and after the night correlated positively with the fractal scaling index α1 during non-REM sleep (p<0.05). These results suggest that RRI dynamics or autonomic nervous system activity during non-REM sleep might be associated with disrupted sleep in patients with CFS.

Source: Togo F, Natelson BH. Heart rate variability during sleep and subsequent sleepiness in patients with chronic fatigue syndrome. Auton Neurosci. 2013 Jun;176(1-2):85-90. doi: 10.1016/j.autneu.2013.02.015. Epub 2013 Mar 15. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4100066/ (Full article)

Psychological stress contributed to the development of low-grade fever in a patient with chronic fatigue syndrome: a case report

Abstract:

BACKGROUND: Low-grade fever is a common symptom in patients with chronic fatigue syndrome (CFS), but the mechanisms responsible for its development are poorly understood. We submit this case report that suggests that psychological stress contributes to low-grade fever in CFS.

CASE PRESENTATION: A 26-year-old female nurse with CFS was admitted to our hospital. She had been recording her axillary temperature regularly and found that it was especially high when she felt stress at work. To assess how psychological stress affects temperature and to investigate the possible mechanisms for this hyperthermia, we conducted a 60-minute stress interview and observed the changes in the following parameters: axillary temperature, fingertip temperature, systolic blood pressure, diastolic blood pressure, heart rate, plasma catecholamine levels, and serum levels of interleukin (IL)-1β and IL-6 (pyretic cytokines), tumor necrosis factor-α and IL-10 (antipyretic cytokines). The stress interview consisted of recalling and talking about stressful events. Her axillary temperature at baseline was 37.2°C, increasing to 38.2°C by the end of the interview. In contrast, her fingertip temperature decreased during the interview. Her heart rate, systolic and diastolic blood pressures, and plasma levels of noradrenaline and adrenaline increased during the interview; there were no significant changes in either pyretic or antipyretic cytokines during or after the interview.

CONCLUSIONS: A stress interview induced a 1.0°C increase in axillary temperature in a CFS patient. Negative emotion-associated sympathetic activation, rather than pyretic cytokine production, contributed to the increase in temperature induced by the stress interview. This suggests that psychological stress may contribute to the development or the exacerbation of low-grade fever in some CFS patients.

Source: Oka T, Kanemitsu Y, Sudo N, Hayashi H, Oka K. Psychological stress contributed to the development of low-grade fever in a patient with chronic fatigue syndrome: a case report. Biopsychosoc Med. 2013 Mar 8;7(1):7. doi: 10.1186/1751-0759-7-7. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3599992/ (Full article)

A narrative review on the similarities and dissimilarities between myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) and sickness behavior

Abstract:

It is of importance whether myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a variant of sickness behavior. The latter is induced by acute infections/injury being principally mediated through proinflammatory cytokines. Sickness is a beneficial behavioral response that serves to enhance recovery, conserves energy and plays a role in the resolution of inflammation.

There are behavioral/symptomatic similarities (for example, fatigue, malaise, hyperalgesia) and dissimilarities (gastrointestinal symptoms, anorexia and weight loss) between sickness and ME/CFS. While sickness is an adaptive response induced by proinflammatory cytokines, ME/CFS is a chronic, disabling disorder, where the pathophysiology is related to activation of immunoinflammatory and oxidative pathways and autoimmune responses.

While sickness behavior is a state of energy conservation, which plays a role in combating pathogens, ME/CFS is a chronic disease underpinned by a state of energy depletion. While sickness is an acute response to infection/injury, the trigger factors in ME/CFS are less well defined and encompass acute and chronic infections, as well as inflammatory or autoimmune diseases. It is concluded that sickness behavior and ME/CFS are two different conditions.

Source: Morris G, Anderson G, Galecki P, Berk M, Maes M. A narrative review on the similarities and dissimilarities between myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) and sickness behavior. BMC Med. 2013 Mar 8;11:64. doi: 10.1186/1741-7015-11-64. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3751187/ (Full article)

A case of lyme disease requiring over 1 year to diagnose at an infectious-disease clinic

Abstract:

A 42-year-old woman presenting with years of fever and vague symptoms could not be satisfactorily diagnosed in physical examination or conventional workups. She was presumptively diagnosed with chronic fatigue syndrome and treated symptomatically. Fourteen months after the initial visit, she developed left facial palsy. Lyme disease serology was positive. Four weeks of oral amoxicillin ameliorated symptoms. Only 5 to 15 cases of Lyme disease are reported annually in Japan, mostly from the northeastern-most island of Hokkaido. It may occur anywhere in Japan, however; probably is underdiagnosed. Lyme disease may cause fevers of unknown origin. Astute clinical suspicion and appropriate workups are thus needed to diagnose this infection.

Source: Iwata K, Shimada T, Kawabata H. A case of lyme disease requiring over 1 year to diagnose at an infectious-disease clinic. Kansenshogaku Zasshi. 2013 Jan;87(1):44-8. [Article in Japanese] https://www.ncbi.nlm.nih.gov/pubmed/23484378

Diagnosis of myalgic encephalomyelitis: where are we now?

Abstract:

INTRODUCTION: The World Health Organization has classified myalgic encephalomyelitis (ME) as a neurological disease since 1969 considering chronic fatigue syndrome (CFS) as a synonym used interchangeably for ME since 1969. ME and CFS are considered to be neuro-immune disorders, characterized by specific symptom profiles and a neuro-immune pathophysiology. However, there is controversy as to which criteria should be used to classify patients with “chronic fatigue syndrome.”

AREAS COVERED: The Centers for Disease Control and Prevention (CDC) criteria consider chronic fatigue (CF) to be distinctive for CFS, whereas the International Consensus Criteria (ICC) stresses the presence of post-exertion malaise (PEM) as the hallmark feature of ME. These case definitions have not been subjected to rigorous external validation methods, for example, pattern recognition analyses, instead being based on clinical insights and consensus.

EXPERT OPINION: Pattern recognition methods showed the existence of three qualitatively different categories: (a) CF, where CF evident, but not satisfying full CDC syndrome criteria. (b) CFS, satisfying CDC criteria but without PEM. (c) ME, where PEM is evident in CFS. Future research on this “chronic fatigue spectrum” should, therefore, use the above-mentioned validated categories and novel tailored algorithms to classify patients into ME, CFS, or CF.

Comment in: Comment and reply on: ME is a distinct diagnostic entity, not part of a chronic fatigue spectrum. [Expert Opin Med Diagn. 2013]

Source: Maes M, Anderson G, Morris G, Berk M. Diagnosis of myalgic encephalomyelitis: where are we now? Expert Opin Med Diagn. 2013 May;7(3):221-5. doi: 10.1517/17530059.2013.776039. Epub 2013 Feb 27. https://www.ncbi.nlm.nih.gov/pubmed/23480562

Altered functional B cell subset populations in patients with chronic fatigue syndrome compared to healthy controls

Abstract:

Chronic fatigue syndrome (CFS) is a heterogeneous disorder of unknown aetiology characterized by disabling fatigue, headaches, sleep disturbance and several other symptoms. The onset of CFS may follow a viral infection or period of stress. Patients with CFS do not have hypogammaglobulinaemia, predisposition to recurrent bacterial infections or symptoms of autoimmunity.

To date, defects in B cell numbers or function have not been shown in the literature. However, treatment with anti-B cell therapy using Rituximab has recently shown benefit to CFS patients. We therefore postulated that patients with CFS had a subtle humoral immune dysfunction, and performed extended B cell immunophenotyping.

We undertook a detailed characterization of the proportions of the different B cell subsets in 33 patients with CFS fulfilling the Canadian and Fukada criteria for CFS and compared these with 24 age- and gender-matched healthy controls (HC). CFS patients had greater numbers of naive B cells as a percentage of lymphocytes: 6·3 versus 3·9% in HC (P = 0·034), greater numbers of naive B cells as a percentage of B cells: 65 versus 47% in controls (P = 0·003), greater numbers of transitional B cells: 1·8 versus 0·8% in controls (P = 0·025) and reduced numbers of plasmablasts: 0·5 versus 0·9% in controls (P = 0·013). While the cause of these changes is unclear, we speculate whether they may suggest a subtle tendency to autoimmunity.

Source: Bradley AS, Ford B, Bansal AS. Altered functional B cell subset populations in patients with chronic fatigue syndrome compared to healthy controls. Clin Exp Immunol. 2013 Apr;172(1):73-80. doi: 10.1111/cei.12043. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3719933/ (Full article)